Using Information Theory to Detect Rogue Taxa and Improve Consensus Trees | Zendy

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Using Information Theory to Detect Rogue Taxa and Improve Consensus Trees

Author(s) -

Martin R. Smith

Publication year - 2021

Publication title -

systematic biology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 7.128

H-Index - 182

eISSN - 1076-836X

pISSN - 1063-5157

DOI - 10.1093/sysbio/syab099

Subject(s) - taxon , phylogenetic tree , biology , congruence (geometry) , set (abstract data type) , tree (set theory) , tree of life (biology) , evolutionary biology , ecology , computer science , mathematics , combinatorics , genetics , geometry , gene , programming language

“Rogue” taxa of uncertain affinity can confound attempts to summarize the results of phylogenetic analyses. Rogues reduce resolution and support values in consensus trees, potentially obscuring strong evidence for relationships between other taxa. Information theory provides a principled means of assessing the congruence between a set of trees and their consensus, allowing rogue taxa to be identified more effectively than when using ad hoc measures of tree quality. A basic implementation of this approach in R recovers reduced consensus trees that are better resolved, more accurate, and more informative than those generated by existing methods. [Consensus trees; information theory; phylogenetic software; Rogue taxa.]

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